3D Asset Generation
Overview
The field studies how to turn sparse visual or language inputs into complete 3D assets, including geometry, textures, materials, parts, and motion. Common approaches adapt diffusion and flow models to 3D representations, combine 2D generative priors with multi-view rendering, or use retrieval, procedural code, and structured part-based generation. A growing focus is making assets editable and usable in animation, games, robotics, and simulation, where articulation, collisions, scale, and physical properties matter alongside appearance. The central challenge is balancing visual fidelity and fast generation with cross-view consistency, structural validity, and reliable evaluation of whether an asset works beyond rendered images.
Latest papers
167 papers25 papers in the last four weeks, up 108% on the four weeks before. 0.1% of all new papers.